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Abstract Purpose Propensity score matching is vital in epidemiological studies using observational data, yet its estimates relies on correct model-specification. This study assesses supervised deep learning models and unsupervised autoencoders for propensity score estimation, comparing them with traditional methods for bias and variance accuracy in treatment effect estimations. Methods Utilizing a plasmode simulation based on the Right Heart Catheterization dataset, under a variety of settings, we evaluated (1) a supervised deep learning architecture and (2) an unsupervised autoencoder, alongside two traditional methods: logistic regression and a spline-based method in estimating propensity scores for matching. Performance metrics included bias, standard errors, and coverage probability. The analysis was also extended to real-world data, with estimates compared to those obtained via a double robust approach. Results The analysis revealed that supervised deep learning models outperformed unsupervised autoencoders in variance estimation while maintaining comparable levels of bias. These results were supported by analyses of real-world data, where the supervised model’s estimates closely matched those derived from conventional methods. Additionally, deep learning models performed well compared to traditional methods in settings where exposure was rare. Conclusion Supervised deep learning models hold promise in refining propensity score estimations in epidemiological research, offering nuanced confounder adjustment, especially in complex datasets. We endorse integrating supervised deep learning into epidemiological research and share reproducible codes for widespread use and methodological transparency.

Objectives: Poverty exposes children to adverse conditions that negatively impact development. However, there is limited understanding on how different types of poverty may affect children of various immigration backgrounds differently in outcomes such as school readiness. This study examined these relationships between household and/or neighbourhood poverty, poverty timing, and immigration background with school readiness outcomes at kindergarten. Methods: This study utilized a retrospective, population-based cohort of administrative records linked with surveys completed by kindergarten teachers for 15 369 children born in British Columbia, Canada. The exposures investigated were neighbourhood poverty (residing in a neighbourhood in the lowest income-quintile) and/or household poverty (receiving a health insurance subsidy due to low household income). Experiencing both neighbourhood and household poverty simultaneously was defined as “combined” household and neighbourhood poverty. The outcome of vulnerability on school readiness domains was assessed at kindergarten (47.8% female; mean age = 6.01 years) using teacher ratings on the Early Development Instrument (EDI). Results: Children exposed to combined poverty between age 0 and 2 had greater odds of being vulnerable in two or more domains of school readiness than children not exposed to any poverty during this period (adjusted odds ratio (aOR) = 2.07, 95% CI: [1.74; 2.47], p

Abstract Background The Gambian Ministry of Health is supportive of HIV self-testing (HIVST) and HIVST initiatives are being piloted as an additional strategy to increase HIV testing for individuals not currently reached by existing services, particularly men. This study aimed to determine awareness of HIVST among Gambian men, and whether prior awareness of HIVST is associated with recent HIV testing uptake. Methods We used men’s cross-sectional data from the 2019–2020 Gambian Demographic and Health Survey. We employed design-adjusted multivariable logistic regression to examine the association between HIVST awareness and recent HIV testing. Propensity-score weighting was conducted as sensitivity analyses. Results Of 3,308 Gambian men included in the study, 11% (372) were aware of HIVST and 16% (450) received HIV testing in the last 12 months. In the design-adjusted multivariable analysis, men who were aware of HIVST had 1.76 times (95% confidence interval: 1.26–2.45) the odds of having an HIV test in the last 12 months, compared to those who were not aware of HIVST. Sensitivity analyses revealed similar findings. Conclusion Awareness of HIVST may help increase the uptake of HIV testing among men in Gambia. This finding highlights HIVST awareness-raising activities to be an important intervention for nationwide HIVST program planning and implementation in Gambia.

Summary: Background: HCV infection is associated with mortality due to extrahepatic manifestations (EHM). Sustained virologic response (SVR) following direct-acting antiviral (DAA) therapy has been linked to decreased all-cause and liver-related mortality. However, evidence regarding the impact of DAA on EHM-related deaths is lacking. This study aimed to assess the impact of DAA and SVR on EHM-related mortality. Methods: The British Columbia Hepatitis Testers Cohort comprises ∼1.7 million people tested for HCV between 1990 and 2015 and is linked with administrative health data. Among individuals diagnosed with HCV by 12/31/2020, those who received at least one DAA treatment were matched to those who never received treatment by the year of their first HCV RNA positive date. We compared three groups: treated & SVR, treated & no-SVR, and untreated; and generated EHM mortality rates and incidence curves. To account for differences in baseline characteristics, we used inverse probability of treatment weights (IPTW). IPTW-weighted multivariable cause-specific Cox regression models were adjusted for competing risk and confounders. Findings: Study population included 12,815 treated (12,287 SVR, 528 no-SVR) and 12,815 untreated individuals (median follow-up 3.4 years, IQR 2.9). The untreated group had the highest EHM mortality rate (30.9 per 1000 person-years [PY], 95% CI 29.2–32.8), followed by the treated & no-SVR group (21.2 per 1000 PY, 95% CI 14.9–30.1), while the treated & SVR group had the lowest EHM mortality rate (7.9 per 1000 PY, 95% CI 7.1–8.7). In the multivariable model, EHM mortality in the treated & SVR group was significantly decreased (adjusted cause-specific hazard ratio [acsHR] 0.20, 95% CI 0.18–0.23). The treated & SVR group had significant reductions in mortality related to each of the EHMs (78–84%). Interpretation: Treatment of HCV with DAA was associated with significant reductions in EHM-related mortality. These findings emphasize the critical importance of timely diagnosis and treatment of HCV to prevent deaths associated with EHM, and have important implications for clinical practice and public health. Funding: This work was supported by the BC Centre for Disease Control and the Canadian Institutes of Health Research (CIHR) [Grant # NHC-348216, PJT-156066, and PHE-337680]. DJ has received Doctoral Research Award (#201910DF1-435705-64343) from the Canadian Institutes of Health Research (CIHR) and Doctoral fellowship from the Canadian Network on Hepatitis C (CanHepC). CanHepC is funded by a joint initiative of the Canadian Institutes of Health Research (CIHR) (NHC-142832) and the Public Health Agency of Canada (PHAC).

Abstract Background and purpose Studies of carotid endarterectomy (CEA) require stratification by symptomatic vs asymptomatic status because of marked differences in benefits and harms. In administrative datasets, this classification has been done using hospital discharge diagnosis codes of uncertain accuracy. This study aims to develop and evaluate algorithms for classifying symptomatic status using hospital discharge and physician claims data. Methods A single center’s administrative database was used to assemble a retrospective cohort of participants with CEA. Symptomatic status was ascertained by chart review prior to linkage with physician claims and hospital discharge data. Accuracy of rule-based classification by discharge diagnosis codes was measured by sensitivity and specificity. Elastic net logistic regression and random forest models combining physician claims and discharge data were generated from the training set and assessed in a test set of final year participants. Models were compared to rule-based classification using sensitivity at fixed specificity. Results We identified 971 participants undergoing CEA at the Vancouver General Hospital (Vancouver, Canada) between January 1, 2008 and December 31, 2016. Of these, 729 met inclusion/exclusion criteria (n = 615 training, n = 114 test). Classification of symptomatic status using hospital discharge diagnosis codes was 32.8% (95% CI 29–37%) sensitive and 98.6% specific (96–100%). At matched 98.6% specificity, models that incorporated physician claims data were significantly more sensitive: elastic net 69.4% (59–82%) and random forest 78.8% (69–88%). Conclusion Discharge diagnoses were specific but insensitive for the classification of CEA symptomatic status. Elastic net and random forest machine learning algorithms that included physician claims data were sensitive and specific, and are likely an improvement over current state of classification by discharge diagnosis alone.

IntroductionAdherence to cancer prevention recommendations can greatly reduce colorectal cancer risk. This study explored patterns and determinants of adherence to these recommendations by participants (n = 26 074) at baseline in a cohort study in British Columbia, Canada. MethodsAdherence to five colorectal cancer primary prevention behaviours derived from Canadian Cancer Society/World Cancer Research Fund recommendations (nonsmoking, body mass index (BMI), physical activity, alcohol consumption and fruit and vegetable consumption) was measured, and a composite score constructed based on their sum. The definition of secondary prevention adherence was based on the Canadian Task Force on Preventive Health Care recommendations for colorectal cancer screening. ResultsAdherence to primary prevention guidelines ranged from 94.8% (nonsmoking) to 44.2% (healthy BMI). Median composite score was 4. Higher composite scores were associated with being female, being married and with a higher educational attainment. Colorectal cancer screening adherence was 62.4%. Older age, chronic conditions, a recent medical examination and higher income were associated with greater odds of adherence to screening. ConclusionAdherence to some colorectal cancer prevention behaviours was high, consistent with findings that British Columbia has low rates of many risky health behaviours. However, there was a clustering of poorer adherence to prevention behaviours with each other and with other risk factors. Screening adherence was high but varied with some sociodemographic and health factors. Future work should evaluate targeted interventions to improve adherence among those in the lowest socioeconomic status and health groups. A better understanding is also needed of the barriers to access and engagement with colorectal cancer screening that persist even in the Canadian public health care system.

IntroductionL’adhésion aux recommandations en matière de prévention du cancer peut grandement réduire le risque de cancer colorectal. Cette étude porte sur les tendances et les déterminants de l’adhésion à ces recommandations par les participants (n = 26 074) au début d’une étude de cohorte en Colombie‑Britannique (Canada). MéthodologieNous avons mesuré l’adhésion à cinq comportements de prévention primaire du cancer colorectal tirés des recommandations émises par la Société canadienne du cancer et le Fonds mondial de recherche contre le cancer (absence de tabagisme, indice de masse corporelle (IMC), activité physique, consommation d’alcool et consommation de fruits et légumes) et nous avons établi un score composite reposant sur la somme des mesures. La définition de l’adhésion aux comportements de prévention secondaire est fondée sur les recommandations du Groupe d’étude canadien sur les soins de santé préventifs pour le dépistage du cancer colorectal. RésultatsL’adhésion aux lignes directrices en matière de prévention primaire variait entre 94,8 % (absence de tabagisme) à 44,2 % (IMC santé). Le score composite médian était de 4. Les scores composites supérieurs ont été associés au fait d’être une femme, d’être marié(e) et d’avoir un niveau de scolarité plus élevé. Le taux d’adhésion au dépistage du cancer colorectal était de 62,4 %. Un âge avancé, la présence de maladies chroniques, le fait d’avoir subi un examen médical récemment et le fait de faire partie d’un ménage à revenu élevé étaient associés à une probabilité accrue d’adhésion au dépistage. ConclusionL’adhésion à certains comportements de prévention du cancer colorectal s’est révélée élevée, ce qui concorde avec les constatations selon lesquelles la Colombie-Britannique affiche des taux faibles pour de nombreux comportements risqués pour la santé. Cependant, on a constaté une agglomération de plus faible adhésion aux comportements de prévention les uns avec les autres et en présence d’autres facteurs de risque. L’adhésion au dépistage s’est révélée élevée, mais varie en fonction de certains facteurs sociodémographiques et sanitaires. Les travaux futurs devraient porter sur des interventions ciblées visant à améliorer l’adhésion des individus faisant partie des groupes dont le statut socioéconomique et l’état de santé sont les plus précaires. Il faut également mieux comprendre les obstacles à l’accès et à la participation au dépistage du cancer colorectal, qui persistent même au sein du système de santé public canadien.

Abstract Background Two-stage least square [2SLS] and two-stage residual inclusion [2SRI] are popularly used instrumental variable (IV) methods to address medication nonadherence in pragmatic trials with point treatment settings. These methods require assumptions, e.g., exclusion restriction, although they are known to handle unmeasured confounding. The newer IV-method, nonparametric causal bound [NPCB], showed promise in reducing uncertainty compared to usual IV-methods. The inverse probability-weighted per-protocol [IP-weighted PP] method is useful in the same setting but requires different assumptions, e.g., no unmeasured confounding. Although all of these methods are aimed to address the same nonadherence problem, comprehensive simulations to compare performances of them are absent in the literature. Methods We performed extensive simulations to compare the performances of the above methods in addressing nonadherence when: (1) exclusion restriction satisfied and no unmeasured confounding, (2) exclusion restriction is met but unmeasured confounding present, and (3) exclusion restriction is violated. Our simulations varied parameters such as, levels of adherence rates, unmeasured confounding, and exclusion restriction violations. Risk differences were estimated, and we compared performances in terms of bias, standard error (SE), mean squared error (MSE), and 95% confidence interval coverage probability. Results For setting (1), 2SLS and 2SRI have small bias and nominal coverage. IP-weighted PP outperforms these IV-methods in terms of smaller MSE but produces high MSE when nonadherence is very high. For setting (2), IP-weighted-PP generally performs poorly compared to 2SLS and 2SRI in term of bias, and both-stages adjusted IV-methods improve precision than naive IV-methods. For setting (3), IV-methods perform worst in all scenarios, and IP-weighted-PP produces unbiased estimates and small MSE when confounders are adjusted. NPCB produces larger uncertainty bound width in almost all scenarios. We also analyze a two-arm trial to estimate vitamin-A supplementation effect on childhood mortality after addressing nonadherence. Conclusions Understanding finite sample characteristics of these methods will guide future researchers in determining suitable analysis strategies. Since assumptions are different and often untestable for IP-weighted PP and IV methods, we suggest analyzing data using both IP-weighted PP and IV approaches in search of a robust conclusion.

BackgroundRecent data have demonstrated that healthcare use after treatment for respiratory tuberculosis (TB) remains elevated in the years following treatment completion. However, it remains unclear which TB survivors are high healthcare users and whether any variation exists within this population. Thus, the primary objective of this study was to identify distinct profiles of high healthcare-use TB survivors to help inform post-treatment support and care.MethodsUsing linked health administrative data from British Columbia, Canada, we identified foreign-born individuals who completed treatment for incident respiratory TB between 1990 and 2019. We defined high healthcare-use TB survivors as those in the top 10% of annual emergency department visits, hospital admissions, or general practitioner visits among the study population during the five-year period immediately following TB treatment completion. We then used latent class analysis to categorize the identified high healthcare-use TB survivors into subgroups.ResultsOf the 1,240 people who completed treatment for respiratory TB, 258 (20.8%) people were identified as high post- TB healthcare users. Latent class analysis results in a 2-class solution. Class 1 (n = 196; 76.0%) included older individuals (median age 71.0; IQR 59.8, 79.0) with a higher probability of pre-existing hypertension and diabetes (41.3% and 33.2%, respectively). Class 2 (n = 62; 24.0%) comprised of younger individuals (median age 31.0; IQR 27.0, 41.0) with a high probability (61.3%) of immigrating to Canada within five years of their TB diagnosis and a low probability (11.3%) of moderate to high continuity of primary care.DiscussionOur findings suggest that foreign-born high healthcare-use TB survivors in a high-resource setting may be categorized into distinct profiles to help guide the development of person-centred care strategies targeting the long-term health impacts TB survivors face.

Background and objectivesLittle is known of the potential sex and age differences in the MS prodrome. We investigated sex and age differences in healthcare utilization during the MS prodrome.MethodsThis was a population-based matched cohort study linking administrative and clinical data from British Columbia, Canada (population = 5 million). MS cases in the 5 years preceding a first demyelinating event (“administrative cohort;” n = 6,863) or MS symptom onset (“clinical cohort;” n = 966) were compared to age-, sex- and geographically-matched controls (n = 31,865/4,534). Negative binomial and modified Poisson models were used to compare the rates of physician visits and hospitalizations per international classification of diseases chapter, and prescriptions filled per drug class, between MS cases and controls across sex and age-groups (< 30, 30–49, ≥50 years).ResultsIn the administrative cohort, males with MS had a higher relative rate for genitourinary-related visits (males: adjusted Rate Ratio (aRR) = 1.65, females: aRR = 1.19, likelihood ratio test P = 0.02) and antivertigo prescriptions (males: aRR = 4.72, females: aRR = 3.01 P < 0.01). Injury and infection-related hospitalizations were relatively more frequent for ≥50-year-olds (injuries < 30/30–49/≥50: aRR = 1.16/1.39/2.12, P < 0.01; infections 30–49/≥50: aRR = 1.43/2.72, P = 0.03), while sensory-related visits and cardiovascular prescriptions were relatively more common in younger persons (sensory 30–49/≥50: aRR = 1.67/1.45, P = 0.03; cardiovascular < 30/30–49/≥50: aRR = 1.56/1.39/1.18, P < 0.01). General practitioner visits were relatively more frequent in males (males: aRR = 1.63, females: aRR = 1.40, P < 0.01) and ≥50-year-olds (< 30/≥50: aRR = 1.32/1.55, P = 0.02), while differences in ophthalmologist visits were disproportionally larger among younger persons, < 50-years-old (< 30/30–49/≥50: aRR = 2.25/2.20/1.55, P < 0.01). None of the sex and age-related differences in the smaller clinical cohort reached significance (P ≥ 0.05).DiscussionSex and age-specific differences in healthcare use were observed in the 5 years before MS onset. Findings demonstrate fundamental heterogeneity in the MS prodromal presentation.

ABSTRACT SARS-CoV-2 anti-spike antibody concentrations and angiotensin converting enzyme-2 (ACE-2) inhibition have been used as surrogates to live viral neutralizing antibody titers; however, validity among vaccinated individuals is unclear. We tested the correlation of these measures among vaccinated participants, and examined subgroups based on duration since vaccination and vaccine dosing intervals. We analyzed 120 samples from two-dose mRNA vaccinees without previous COVID-19. We calculated Spearman correlation coefficients between wild-type viral neutralizing antibody titers and: anti-spike (total and IgG), anti-receptor-binding-domain (RBD), and anti-N-terminal-domain (NTD) antibodies; and ACE-2 binding by RBD. We performed three secondary analyses, dichotomizing samples by the first vaccination-to-blood collection interval, second vaccination-to-blood collection interval, and by the vaccine dosing interval (all groups divided by the median), and compared correlation coefficients (Fisher’s Z test). Of 120 participants, 63 (53%) were women, 91 (76%) and 29 (24%) received BNT162b2 and mRNA-1273 vaccines, respectively. Overall, live viral neutralization was correlated with anti-spike total antibody (correlation coefficient = 0.80), anti-spike IgG (0.63), anti-RBD IgG (0.62), anti-NTD IgG (0.64), and RBD ACE2 binding (0.65). Samples with long (>158 days) first vaccination-to-blood collection and long (>71 days) second vaccination-to-blood collection intervals demonstrated higher correlation coefficients, compared with short groups. When comparing cases divided by short (≤39 days) versus long vaccine dosing intervals, only correlation with RBD-ACE-2 binding inhibition was higher in the long group. Among COVID-negative mRNA vaccinees, anti-spike antibody and ACE-2 inhibition concentrations are correlated with live viral neutralizing antibody titers. Correlation was stronger among samples collected at later durations from vaccination. IMPORTANCE Live viral neutralizing antibody titers are an accepted measure of immunity; however, testing procedures are labor-intensive. COVID-19 antibody and angiotensin converting enzyme-2 (ACE-2) levels have been used as surrogates to live viral neutralizing antibody titers; however, validity among vaccinated individuals is unclear. Using samples from 120 two-dose mRNA vaccinees without previous COVID-19, we found that live viral neutralization was correlated with COVID-19 antibody and ACE2 binding levels. When grouping samples by the time interval between vaccination and sample blood collection, samples collected over 158 days after the first vaccine and over 71 days from the second vaccine demonstrated stronger correlation between live viral neutralization titers and both antibody and ACE2 levels, in comparison to those collected earlier.

The SARS-CoV-2 belongs to the coronavirus family, which also includes common endemic coronaviruses (HCoVs). We hypothesized that immunity to HCoVs would be associated with stronger immunogenicity from SARS-CoV-2 vaccines. The study included samples from the COSRIP observational cohort study of adult paramedics in Canada. Participants provided blood samples, questionnaire data, and results of COVID-19 testing. Samples were tested for anti-spike IgG against SARS-CoV-2, HCoV-229E, HCoV-HKU1, HCoV-NL63, and HCoV-OC43 antigens. We first compared samples from vaccinated and unvaccinated participants, to determine which HCoV antibodies were affected by vaccination. We created scatter plots and performed correlation analysis to estimate the extent of the linear relationship between HCoVs and SARS-CoV-2 anti-spike antibodies. Further, using adjusted log-log multiple regression, we modeled the association between each strain of HCoV and SARS-CoV-2 antibodies. Of 1510 participants (mean age of 39 years), 94 (6.2%) had a history of COVID-19. There were significant differences between vaccinated and unvaccinated participant in anti-spike antibodies to HCoV-HKU1, and HCoV-OC43; however, levels for HCoV-229E and HCoV-NL63 were similar (suggesting that vaccination did not affect these baseline values). Among vaccinated individuals without prior COVID-19 infection, SARS-COV-2 anti-spike IgG demonstrated a weak positive relationship between both HCoV-229E (r = 0.11) and HCoV-NL63 (r = 0.12). From the adjusted log-log multiple regression model, higher HCoV-229E and HCoV-NL63 anti-spike IgG antibodies were associated with increased SARS-COV-2 anti-spike IgG antibodies. Vaccination appears to result in measurable increases in HCoV-HKU1, and HCoV-OC43 IgG levels. Anti-HCoV-229E and HCoV-NL63 antibodies were unaffected by vaccination, and higher levels were associated with significantly higher COVID-19 vaccine-induced SARS-COV-2 antibodies.

Abstract Background Hepatitis C virus (HCV) causes life-threatening chronic infections. Implementation of novel, economical or widely available screening tools can help detect unidentified cases and facilitate their linkage to care. We investigated the relationship between chronic HCV infection and a potential complete blood count biomarker (the monocyte-to-platelet ratio) in the United States. Methods The analytic dataset was selected from cycle years 2009–2016 of the National Health and Nutrition Examination Survey. Complete case data- with no missingness- was available for n = 5281 observations, one-hundred and twenty-two (n = 122) of which were exposed to chronic HCV. The primary analysis used survey-weighted logistic regression to model the effect of chronic HCV on the monocyte-to-platelet ratio adjusting for demographic and biological confounders in a causal inference framework. Missing data and propensity score methods were respectively performed as a secondary and sensitivity analysis. Results In the analytic dataset, outcome data was available for n = 5281 (n = 64,245,530 in the weighted sample) observations of which n = 122 (n = 1,067,882 in the weighted sample) tested nucleic acid positive for HCV. Those exposed to chronic HCV infection in the United States have 3.10 times the odds of a high monocyte-to-platelet ratio than those not exposed (OR = 3.10, [95% CI: 1.55–6.18]). Conclusion A relationship exists between chronic HCV infection and the monocyte-to-platelet ratio in the general population of the United States. Reversing the direction of this association to predict chronic HCV infection from complete blood counts, could provide an economically feasible and universal screening tool, which would help link patients with care.

Abstract Background The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. Methods Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) – the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. Results IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. Conclusions Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

Abstract Background The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. Methods Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. Results Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. Conclusions Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

ABSTRACT SARS-CoV-2 seroprevalence studies may be complicated by vaccination efforts. It is important to characterize the ability of serology methods to correctly distinguish prior infection from postvaccination seroreactivity. We report the performance of the Meso Scale Discovery (MSD) V-PLEX COVID-19 Coronavirus Panel 2 IgG assay. Using serum samples from a prospective cohort of paramedics, we calculated the performance of the V-PLEX nucleocapsid (“N”) assay to classify prior SARS-CoV-2 infections, defined as a (i) history of a positive SARS-CoV-2 PCR test or (ii) positive serology results using the Roche Elecsys total nucleocapsid anti-SARS-Cov-2 assay. We calculated sensitivity and specificity at the optimal threshold (defined by the highest Youden index). We compared subgroups based on vaccination status, and between models that excluded prior infections 3 to 12 months before sample collection. Of 1119 participants, 914 (81.7%) were vaccinated and 60 (5.4%) had evidence of a preceding SARS-CoV-2 infection. Overall and within vaccinated and unvaccinated subgroups, the optimal thresholds were 828 AU/mL, 827 AU/mL, and 1324 AU/mL; with sensitivities of 0.95 (95% CI: 0.94 to 0.96), 0.95 (0.94 to 0.96), 0.94 (0.92 to 0.96) and specificities of 0.88 (0.86 to 0.90), 0.87 (0.85 to 0.89), and 0.94 (0.89 to 0.98), respectively. N-assay specificity was significantly better in unvaccinated (versus vaccinated) individuals (P = 0.005). Overall optimal thresholds based on the AUC values were higher for samples from unvaccinated participants, especially when examining infections within the preceding 9 months (5855 versus 1704 AU/mL). Overall, V-PLEX nucleocapsid assay cutoff values were higher among unvaccinated individuals. Specificity was also significantly higher among unvaccinated individuals. Different thresholds were required to achieve optimal test performance, especially for detecting SARS-CoV-2 infections within the preceding 9 months. IMPORTANCE Among a cohort of adult paramedics in Canada, we investigated the performance of nucleocapsid (N) antibody detection (measured with a V-PLEX assay) to identify previous COVID-19 infections and compared differences among vaccinated and unvaccinated. Our data indicate that vaccinated and unvaccinated groups require different thresholds to achieve optimal test performance, especially for detecting COVID-19 within the preceding 9 months. Overall, specificity was significantly higher among unvaccinated, compared to vaccinated individuals.

Abstract In veneer-drying facilities, controllers face many challenges to maintain desired parameters in the final product based on customer’s needs. The major challenge is setting process parameters to control the temperature and humidity within the various sections in the drying machine to obtain the desired properties of the final product. The regression tree approach can be used to simplify the complex relationship among process and product variables for identifying critical factors for drying veneer and achieving the desired range of veneer temperature. In this study, we investigated veneer-drying conditions and the short-term effect of climatic variables on veneer temperature. We have shown a three-step process to develop an optimal regression tree for veneer temperature. From the developed optimal tree, we are able to identify the most important threshold points of predictor space and adjustment for the climatic variables on the temperature of veneer sheets. The findings of this study were further investigated in an industrial setting and the desired veneer temperatures were attained for the final product. This application shows that we can follow the path of the optimal tree to pinpoint the most desired veneer temperature outcome. The developed optimal tree is relatively easy to use and interpret to estimate the average response of veneer temperature.

Abstract Background In a cross-sectional stepped-wedge trial with unequal cluster sizes, attained power in the trial depends on the realized allocation of the clusters. This attained power may differ from the expected power calculated using standard formulae by averaging the attained powers over all allocations the randomization algorithm can generate. We investigated the effect of design factors and allocation characteristics on attained power and developed models to predict attained power based on allocation characteristics. Method Based on data simulated and analyzed using linear mixed-effects models, we evaluated the distribution of attained powers under different scenarios with varying intraclass correlation coefficient (ICC) of the responses, coefficient of variation (CV) of the cluster sizes, number of cluster-size groups, distributions of group sizes, and number of clusters. We explored the relationship between attained power and two allocation characteristics: the individual-level correlation between treatment status and time period, and the absolute treatment group imbalance. When computational time was excessive due to a scenario having a large number of possible allocations, we developed regression models to predict attained power using the treatment-vs-time period correlation and absolute treatment group imbalance as predictors. Results The risk of attained power falling more than 5% below the expected or nominal power decreased as the ICC or number of clusters increased and as the CV decreased. Attained power was strongly affected by the treatment-vs-time period correlation. The absolute treatment group imbalance had much less impact on attained power. The attained power for any allocation was predicted accurately using a logistic regression model with the treatment-vs-time period correlation and the absolute treatment group imbalance as predictors. Conclusion In a stepped-wedge trial with unequal cluster sizes, the risk that randomization yields an allocation with inadequate attained power depends on the ICC, the CV of the cluster sizes, and number of clusters. To reduce the computational burden of simulating attained power for allocations, the attained power can be predicted via regression modeling. Trial designers can reduce the risk of low attained power by restricting the randomization algorithm to avoid allocations with large treatment-vs-time period correlations.

Abstract Background Maternal and child mortality remain a global health concern despite different interventions that have been implemented to address this issue. Adequate antenatal care (ANC) is crucial in reducing maternal and neonatal morbidity and mortality. However, in Rwanda, there is still suboptimal utilization of ANC services. This study aims to assess the relationship between perceived barriers to accessing health care and inadequate ANC visits among women of reproductive age in Rwanda. Methods This study is cross-sectional using secondary data from the 2014–15 Rwanda demographic and health survey (RDHS). The study included 5876 women aged 15–49 years, and the primary outcome of the investigation was inadequate ANC visits defined as delayed first ANC visit and non-completion of at least four recommended visits during the pregnancy period. The primary exposure was perceived barriers to accessing health care, operationalized using the following 4 variables: distance to the health facility, getting money for treatment, not wanting to go alone and getting permission to go for treatment. A survey-weighted multivariable logistic regression analysis and backward elimination method based on Akaike information criterion (AIC) was used to select the final model. We conducted a number of sensitivity analyses using stratified and weighting propensity score methods and investigated the relationship between the outcome and each barrier to care separately. Results Of 5, 876 women included in the analysis, 53% (3132) aged 20 to 34 years, and 44% (2640) were in the lowest wealth index. Overall, 64% (2375) of women who perceived to have barriers to health care had inadequate ANC visits. In multivariable analysis, women who perceived to have barriers to health care had higher odds of having inadequate ANC visits (OR: 1.14; 95% CI: 0.99, 1.31). However, the association was borderline statistically significant. The findings from sensitivity analyses were consistent with the main analysis results. Conclusion The study suggests a positive association between perceived barriers to health care access and inadequate ANC visits. The findings speak to a need for interventions that focus on improving access to health care in Rwanda to increase uptake of ANC services.

Purpose: Much of the extant research on quality-of-life (QoL) in homelessness has focused narrowly on health-related QoL. Far less is known about broader subjective quality-of-life (SQoL). The purpose of this study was to examine levels and predictors of SQoL among homeless and vulnerably housed individuals in a 4-year longitudinal study. Methods: Data were from the Health and Housing in Transition (HHiT) study, a prospective cohort study of 1190 individuals from three Canadian cities who were homeless or vulnerably housed. SQoL was measured using a scale designed specifically for this population. Predictor variables were time-varying indicators of housing status, substance use, and social support as well as baseline measures of physical and mental health problems. Generalized estimating equation (GEE) analysis examined these predictors of SQoL, adjusting for baseline age, gender, ethnicity, employment, income, and city of residence. Results: Participants at baseline were 18 to 80 years old (M = 42.2; SD = 10.6), 66% male, 63% White, 60% unemployed, and 50% were currently homeless. Most areas of SQoL tended toward slight satisfaction, with dissatisfaction concerning finance and employment as notable exceptions. Demographic variables were not associated with SQoL. Homelessness and self-reported presence of 3+ chronic health conditions, mental health problems, and problematic substance use, as well as lower perceived social support, were independently associated with lower SQoL. Conclusions: SQoL shows variation across different life areas for homeless and vulnerably housed individuals. In order to improve SQoL in this population, it is important to address poverty, employment, housing challenges, mental and physical health problems, and substance use as well as increase social supports.

Most oropharyngeal and anogenital cancers are caused by human papillomavirus (HPV). Although HPV vaccines showed high efficacy against oropharyngeal and anogenital HPV infections, and cancer precursors in randomized clinical trials, there are limited data on the effectiveness of HPV vaccination against HPV-related cancers. We aimed to evaluate the association of HPV vaccination with HPV-related cancers among a nationally representative sample of United States adults, aged 20–59 years. In a cross-sectional study combining four cycles from the National Health and Nutrition Examination Survey, from 2011 through 2018, we used a survey-weighted logistic regression model, propensity score matching and multiple imputations by chained equations to explore the association of HPV vaccination with HPV-related cancers. Among 9891 participants, we did not find an association of HPV vaccination with HPV-related cancers (adjusted OR = 0.58, 95% CI 0.19; 1.75). Despite no statistically significant association between HPV vaccination and HPV-related cancers, our study findings suggest that HPV-vaccinated adults might have lower odds of developing HPV-related cancers than those who were not vaccinated. Given the importance of determining the impact of vaccination on HPV-related cancers, there is a need to conduct future research by linking cancer registry data with vaccination records, to obtain more robust results.

Data on the contribution of hepatitis B virus (HBV) infection and related comorbidities to liver-related mortality in Canada are limited. We assessed the concurrent impact of HBV infection, non-alcoholic fatty liver disease (NAFLD), and hepatitis C virus (HCV) coinfection on liver-related deaths in British Columbia (BC), Canada. We used data from the BC Hepatitis Testers Cohort (BC-HTC). We used Fine–Gray multivariable sub-distributional hazards models to assess the effect of HBV, NAFLD, and HCV coinfection on liver-related mortality, while adjusting for confounders and competing mortality risks. The liver-related mortality rate was higher among people with HBV infection than those without (2.57 per 1000 PYs (95%CI: 2.46, 2.69) vs. 0.62 per 1000 PYs (95%CI: 0.61, 0.64), respectively). Compared with the HBV negative groups, HBV infection was associated with increased liver-related mortality risk in almost all of the subgroups: HBV mono-infection (adjusted subdistribution hazards ratio (asHR) of 3.35, 95% CI 3.16, 3.55), NAFLD with HBV infection, (asHR 12.5, 95% CI 7.08, 22.07), and HBV/HCV coinfection (asHR 8.4, 95% CI 7.62, 9.26). HBV infection is associated with a higher risk of liver-related mortality, and has a greater relative impact on people with NAFLD and those with HCV coinfection. The diagnosis and treatment of viral and fatty liver disease are required to mitigate liver-related morbidity and mortality.

Introduction Increasing evidence indicates that chronic hepatitis C virus (HCV) infection is associated with higher risk of diabetes. Previous studies showed ethnic disparities in the disease burden of diabetes, with increased risk in Asian population. We described the incidence of type 2 diabetes related to HCV infection and assessed the concurrent impact of HCV infection and ethnicity on the risk of diabetes.Research design and methods In British Columbia Hepatitis Testers Cohort, individuals were followed from HCV diagnosis to the earliest of (1) incident type 2 diabetes, (2) death or (3) end of the study (December 31, 2015). Study population included 847 021 people. Diabetes incidence rates in people with and without HCV were computed. Propensity scores (PS) analysis was used to assess the impact of HCV infection on newly acquired diabetes. PS-matched dataset included 117 184 people. We used Fine and Gray multivariable subdistributional hazards models to assess the effect of HCV and ethnicity on diabetes while adjusting for confounders and competing risks.Results Diabetes incidence rates were higher among people with HCV infection than those without. The highest diabetes incidence rate was in South Asians with HCV (14.7/1000 person-years, 95% CI 12.87 to 16.78). Compared with Others, South Asians with and without HCV and East Asians with HCV had a greater risk of diabetes. In the multivariable stratified analysis, HCV infection was associated with increased diabetes risk in all subgroups: East Asians, adjusted HR (aHR) 3.07 (95% CI 2.43 to 3.88); South Asians, aHR 2.62 (95% CI 2.10 to 3.26); and Others, aHR 2.28 (95% CI 2.15 to 2.42).Conclusions In a large population-based linked administrative health data, HCV infection was associated with higher diabetes risk, with a greater relative impact in East Asians. South Asians had the highest risk of diabetes. These findings highlight the need for care and screening for HCV-related chronic diseases such as type 2 diabetes among people affected by HCV.

Abstract Health researchers are familiar with the concept of trial power, a number that prior to the start of a trial is intended to describe the probability that the results of the trial will correctly conclude that the intervention has an effect. Trial power, as calculated using standard software, is an expected power that arises from averaging hypothetical trial results over all possible treatment allocations that could be generated by the randomization algorithm. However, in the trial that ultimately is conducted, only one treatment allocation will occur, and the corresponding attained power (conditional on the allocation that occurred) is not guaranteed to be equal to the expected power and may be substantially lower. We provide examples illustrating this issue, discuss some circumstances when this issue is a concern, define and advocate the examination of the pre-randomization power distribution for evaluating the risk of obtaining unacceptably low attained power, and suggest the use of randomization restrictions to reduce this risk. In trials that randomize only a modest number of units, we recommend that trial designers evaluate the risk of getting low attained power and, if warranted, modify the randomization algorithm to reduce this risk.

Background: To inform World Health Organization (WHO) global guidelines, we updated and expanded the evidence base to assess the comparative efficacy, tolerability, and safety of first-line antiretroviral therapy (ART) regimens. Methods: We searched Embase, Medline and CENTRAL on 28 February 2020 to update the systematic literature review of clinical trials comparing recommended first-line ART that informed previous WHO guidelines. Outcomes included viral suppression, change in CD4 cell counts, mortality, serious and overall adverse events (AEs), discontinuation, discontinuations due to AEs (DAEs); and new outcomes: drug-resistance, neuropsychiatric AEs, early viral suppression, weight gain and birth outcomes. Comparative effects were assessed through network meta-analyses and certainty in the evidence was assessed using the GRADE framework. Findings: We identified 156 publications pertaining to 68 trials for the primary population. Relative to efavirenz, dolutegravir had improved odds of viral suppression across all time points (odds ratio [OR]: 1·94; 95% credible interval [CrI]: 1·48–2·56 at 96 weeks); was protective of drug-resistance (OR: 0·13; 95%CrI: 0·04–0·48); and led to fewer discontinuations (OR: 0·58; 95%CrI: 0·48–0·70). Evidence supported dolutegravir use among TB-HIV co-infected persons and pregnant women. Adverse birth outcomes were observed in 33.2% of dolutegravir-managed pregnancies and 35.0% of efavirenz-managed pregnancies. Low-dose efavirenz had comparable efficacy and safety to standard-dose efavirenz, but led to fewer DAEs (OR: 0·70; 95%CrI: 0·50–0·92). Interpretation: The evidence supports choosing dolutegravir in combination with lamivudine/emtricitabine and tenofovir disoproxil fumarate as the preferred first-line regimen and low-dose efavirenz-based regimens as an alternative. Dolutegravir can be considered to be effective, safe and tolerable. Funding: WHO.

Rapid social, economic, and environmental changes in the northern territories of Canada have raised concerns about potentially increasing levels of chronic disease. This concern prompted us to compare multimorbidity prevalence in Canada between the territories and provinces. We analyzed Canadian Community Health Survey data for 2013/14. We defined multimorbidity, the outcome, as having 3 or more chronic conditions and used survey-weighted multivariable logistic regression for comparisons between territories and provinces. We found a prevalence of multimorbidity in Canada of 14.0% (95% CI: 13.6, 14.3). We could not find significant difference in multimorbidity prevalence between the territories and provinces of Canada overall; however, the territories tended to have lower prevalence estimates than provinces for multimorbidity (adj-OR = 0.88; 95% CI: 0.74–1.04). Sensitivity analyses from propensity score analyses had similar conclusions. Effect modification analyses identified lower multimorbidity in territories versus provinces among households without a post-secondary graduate (adj-OR = 0.46; 95% CI: 0.34–0.61 for northern residence), males (adj-OR = 0.71; 95% CI: 0.54–0.93), and ages 12–29 years (adj-OR = 0.63; 95% CI: 0.39–0.99). Caution is needed in interpreting the results in light of representativeness of CCHS in northern populations of Canada.

Introduction Longitudinal studies ascertain exposure, covariates, and outcomes over time. For estimating treatment effect on mortality, ignoring the time-varying nature of an exposure may lead to immortal time bias. Time-dependent confounding that affects future treatment may bias the estimated effects. Differences in baseline prognosis between treatment groups further complicate this issue. Objectives and Approach We applied sequential Cox modeling to estimate the causal effect of referral for nephrology care on the survival of adults with advanced chronic kidney disease, linking laboratory and administrative data from Alberta, Canada. We created pseudo-data by mimicking successive randomized controlled trials. To address immortal time bias, each “mini-trial” consisted of individuals starting treatment, and those not yet treated, in each 3-month time interval. We incorporated inverse-probability-of-treatment-weights (IPTW) to minimize treatment selection bias for each “mini-trial. ” We fit a “mini-trial”-stratified, weighted Cox model to estimate the overall hazard ratio for death by averaging the effect estimates across “mini-trials.” Results We included 9,675 patients who entered the cohort between 2002 and 2013. The mean age was 82 years; 35% were male; and 33% were ultimately referred to a nephrologist after a median wait-period of 6 months. Compared to non-referred patients, those referred were younger and had fewer comorbidities at baseline. Referral was associated with a significant 45% lower hazard for death in an adjusted Cox model. The effect was attenuated in a multivariate Cox model with a time-varying exposure and in a sequential Cox model further controlling for potential time-dependent confounding by measures reflecting kidney-, cardiovascular-, and cerebrovascular-health. After incorporating IPTW for addressing treatment selection bias in the same sequential Cox model, the effect estimate was toward the null and no longer significant. Conclusion/Implications We found that applying analytical strategies that addressed immortal time bias, time-dependent confounding, and treatment selection bias, the survival benefit associated with nephrology referral was attenuated. Inverse-probability-of treatment weighted sequential Cox approach may be used to address these important biases and confounding that are common in real-world clinical settings.